Distortion-invariant pattern recognition algorithms in the presence of environmental degradation of the input image

Francis Chan; Bahram Javidi

doi:10.1117/12.326802

9 October 1998 Distortion-invariant pattern recognition algorithms in the presence of environmental degradation of the input image

Francis Chan, Bahram Javidi

Author Affiliations +

Proceedings Volume 3466, Algorithms, Devices, and Systems for Optical Information Processing II; (1998) https://doi.org/10.1117/12.326802
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

The presence of turbulence such as maritime aerosols between the target and the observer degrades the detection and classification performance of electro-optical sensors and detectors. A filtering algorithm that takes into account of the environmental degradation, the background non-overlapping noise, the non-stationarity of the scene, non-target objects and additive system noise is designed and implemented to detect and classify targets under such conditions. The detection performance of this algorithm has been validated using computer simulations and found to be superior to filters that are optimal with respect to noise statistics but do not take into account the effects of environmental conditions. The algorithm is then extended using a set of training images to be distortion-invariant with respect to different target aspects.

Citation Download Citation

Francis Chan and Bahram Javidi "Distortion-invariant pattern recognition algorithms in the presence of environmental degradation of the input image", Proc. SPIE 3466, Algorithms, Devices, and Systems for Optical Information Processing II, (9 October 1998); https://doi.org/10.1117/12.326802

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